The present invention relates in general to supporting creation of a search query, and more specifically, to providing a graphical user interface for simplifying creation, correction, and verification of a search query having a complicated logical structure.
A great many text documents are stored in companies from day to day. Examples include call center contact histories, users' responses to questionnaires, trouble reports, quality information, and sales journals. In recent years, many companies perform the following work-improving cycle using such text information to increase customer satisfaction and reduce corporate risks. First, a large volume of accumulated text information is analyzed by a computer, from which some information related to customer satisfaction and corporate risks is obtained. Next, an action plan is created and executed on the basis of the information obtained. Thereafter, the effects of the executed action plan are verified by analyzing the text information. As a result, if it is determined that expected effects have not been obtained, a hypothesis for its cause is set up by further analyzing the text information, and a new action plan is created and executed on the basis of it.
What is essential in such a work-improving cycle is a technique called text mining in which tacit knowledge present in a text group is turned into explicit knowledge, a certain feature or tendency is found in a text group, or correlation is found between different kinds of text groups.
Here, a document search operation that analysts who are specialized in text mining usually perform will be described using an example of an analyst of a mobile phone company who focuses attention on damage to mobile phones caused by water. The analyst first selects a sample document that describes “damage caused by water” from stored text (for example, complaint mails sent to a support center) and extracts therefrom a specific keyword or sentence pattern common to the description of “damage caused by water”. Next, the analyst creates a search query from the extracted keyword or sentence pattern using a suitable search rule. Finally, the analyst issues the created search query to a document search engine to perform a search to thereby check the content of hit text group in detail.
If the hit text group does not include many expected documents, it shows that the created search query is not suitable. In such a case, the analyst corrects the search query and issues it again to the search engine to perform a search. The analyst repeats the series of operations and stores a search query with which many expected documents can be obtained as a search query for “damage caused by water”.
Thereafter, the analyst performs continuous searches for a text group sent from users, continuously using the created and stored search query, and accumulates hit documents. By analyzing the information accumulated in this way, the analyst finds a measure of “damage caused by water”, on the basis of which the analyst creates an action plan.